Scatter plots in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ visualization

intermediate

Choosing the correct axis for a scatter plot

You want to create a scatter plot in Power BI to analyze sales performance. You have two numeric columns: Sales Amount and Number of Customers. Which should you place on the X-axis and which on the Y-axis for best practice?

A X-axis: Sales Amount, Y-axis: Number of Customers

B X-axis: Sales Amount, Y-axis: Sales Amount

C X-axis: Number of Customers, Y-axis: Sales Amount

D X-axis: Number of Customers, Y-axis: Number of Customers

💡 Hint

Think about which variable is independent and which is dependent.

Number of Customers is usually the independent variable (X-axis), and Sales Amount depends on it (Y-axis). This helps see how sales change with customer count.

❓ dax_lod_result

intermediate

Calculate average sales per customer for scatter plot

You want to add a measure to your scatter plot that shows Average Sales per Customer. Which DAX formula correctly calculates this?

A Average Sales per Customer = SUM(Sales[Sales Amount]) * SUM(Sales[Number of Customers])

B Average Sales per Customer = AVERAGE(Sales[Sales Amount]) / AVERAGE(Sales[Number of Customers])

C Average Sales per Customer = SUM(Sales[Sales Amount]) - SUM(Sales[Number of Customers])

D Average Sales per Customer = DIVIDE(SUM(Sales[Sales Amount]), SUM(Sales[Number of Customers]))

💡 Hint

Think about total sales divided by total customers.

DIVIDE(SUM(Sales[Sales Amount]), SUM(Sales[Number of Customers])) safely calculates average sales per customer.

❓ data_modeling

advanced

Modeling data for scatter plot with categories

You want to create a scatter plot showing sales amount vs number of customers, colored by Region. Your data model has a Sales table and a separate Regions table. What is the best way to model this for the scatter plot?

A Create a relationship between Sales[RegionID] and Regions[RegionID], then use Regions[RegionName] as legend in scatter plot.

B Merge Sales and Regions tables into one table before creating the scatter plot.

C Use Sales[RegionID] directly as legend without any relationship.

D Create a relationship between Sales[Sales Amount] and Regions[RegionName].

💡 Hint

Think about how tables connect in Power BI.

Creating a relationship between Sales and Regions tables on RegionID allows using RegionName as legend properly.

🔧 Formula Fix

advanced

Identify the error in scatter plot measure

You wrote this DAX measure to calculate average sales per customer for a scatter plot:

Avg Sales per Customer = SUM(Sales[Sales Amount]) / COUNT(Sales[CustomerID])

But the scatter plot shows incorrect values. What is the likely problem?

Power BI

Avg Sales per Customer = SUM(Sales[Sales Amount]) / COUNT(Sales[CustomerID])

A SUM cannot be divided by COUNT; use AVERAGE instead.

B COUNT counts all rows including duplicates, so it undercounts customers; use DISTINCTCOUNT instead.

C The measure should use MAX instead of SUM for Sales Amount.

D The formula is correct; the problem is with the scatter plot settings.

💡 Hint

Think about counting unique customers.

COUNT counts all rows, including duplicates. DISTINCTCOUNT counts unique customers, which is needed for average per customer.

🧠 Conceptual

expert

Interpreting scatter plot clusters in sales data

You created a scatter plot with Sales Amount on Y-axis and Number of Customers on X-axis. You notice three distinct clusters of points:

• Cluster 1: Low customers, low sales
• Cluster 2: High customers, medium sales
• Cluster 3: Medium customers, high sales

What is the best interpretation of these clusters?

A Cluster 1 represents small stores, Cluster 2 represents stores with many customers but low sales per customer, Cluster 3 represents stores with fewer customers but high sales per customer.

B Cluster 1 represents stores with high sales efficiency, Cluster 2 represents stores with low customer count, Cluster 3 represents stores with average sales and customers.

C Clusters show random data with no meaningful pattern.

D Cluster 1 and 3 represent the same type of stores, Cluster 2 is an outlier.

💡 Hint

Think about sales per customer in each cluster.

Cluster 1 has low customers and sales, likely small stores. Cluster 2 has many customers but medium sales, so sales per customer is low. Cluster 3 has medium customers but high sales, so sales per customer is high.

Practice

1. What is the main purpose of a scatter plot in Power BI?

easy

A. To show the relationship between two numeric variables

B. To display data in a pie chart format

C. To list data in rows and columns

D. To create a map visualization

Solution

1. Step 1: Understand scatter plot basics

   A scatter plot uses two numeric axes to show how two variables relate to each other.

2. Step 2: Compare with other chart types

   Pie charts show parts of a whole, tables list data, and maps show locations, not relationships between numbers.

3. Final Answer:

   To show the relationship between two numeric variables -> Option A

4. Quick Check:

   Scatter plot = relationship between numbers [OK]

Hint: Scatter plots always compare two numeric values [OK]

Common Mistakes:

• Confusing scatter plots with pie charts
• Thinking scatter plots show categories only
• Using scatter plots for non-numeric data

2. Which of the following is the correct way to assign data fields in a Power BI scatter plot?

easy

A. Assign date data to Size and text data to X Axis

B. Assign text data to X Axis and Y Axis, numeric data to Legend

C. Assign numeric data to Legend only

D. Assign numeric data to X Axis and Y Axis, optional Legend for categories

Solution

1. Step 1: Identify correct field types for axes

   Scatter plots require numeric data on X and Y axes to plot points in 2D space.

2. Step 2: Understand optional fields

   Legend can be used for categories (text), and Size can represent numeric values for point size.

3. Final Answer:

   Assign numeric data to X Axis and Y Axis, optional Legend for categories -> Option D

4. Quick Check:

   Numeric on axes + Legend for categories [OK]

Hint: X and Y axes must be numeric for scatter plots [OK]

Common Mistakes:

• Putting text data on X or Y axes
• Using Legend for numeric axes
• Assigning date data incorrectly

3. Given a scatter plot with Sales on X Axis and Profit on Y Axis, what pattern would you expect if higher sales generally lead to higher profit?

medium

A. Points are randomly scattered with no pattern

B. Points form a horizontal line

C. Points trend upward from left to right

D. Points trend downward from left to right

Solution

1. Step 1: Understand relationship between Sales and Profit

   If higher sales lead to higher profit, as sales increase (X axis), profit (Y axis) should also increase.

2. Step 2: Visualize the scatter plot pattern

   This creates an upward trend from left (low sales) to right (high sales).

3. Final Answer:

   Points trend upward from left to right -> Option C

4. Quick Check:

   Positive correlation = upward trend [OK]

Hint: Positive correlation means points go up left to right [OK]

Common Mistakes:

• Confusing upward and downward trends
• Expecting horizontal line for correlation
• Ignoring relationship direction

4. You created a scatter plot but all points appear in a single vertical line. What is the most likely cause?

medium

A. X Axis has the same value for all data points

B. Y Axis has the same value for all data points

C. Legend field is missing

D. Size field is assigned text data

Solution

1. Step 1: Analyze vertical line pattern

   A vertical line means all points share the same X coordinate but vary in Y.

2. Step 2: Identify cause in data assignment

   If X Axis data is constant for all points, they align vertically.

3. Final Answer:

   X Axis has the same value for all data points -> Option A

4. Quick Check:

   Same X value = vertical line [OK]

Hint: Same X values cause vertical line in scatter plot [OK]

Common Mistakes:

• Thinking missing Legend causes vertical line
• Confusing vertical with horizontal line causes
• Assigning text to Size field causing this

5. You want to highlight different product categories in a scatter plot showing Sales (X Axis) vs Profit (Y Axis). Which field should you add to best achieve this?

hard

A. Add Product Category to X Axis

B. Add Product Category to Legend

C. Add Product Category to Size

D. Add Product Category to Y Axis

Solution

1. Step 1: Understand how to differentiate categories visually

   Legend assigns colors or markers to categories, making groups visible in scatter plots.

2. Step 2: Evaluate other field assignments

   Adding categories to Size or axes is incorrect because axes require numeric data, and Size is numeric for point size.

3. Final Answer:

   Add Product Category to Legend -> Option B

4. Quick Check:

   Legend = category colors in scatter plot [OK]

Hint: Use Legend for categories to color points [OK]

Common Mistakes:

• Putting categories on numeric axes
• Using Size for categories instead of numeric values
• Not using Legend to differentiate groups